WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

Permanent URI for this collectionhttps://hdl.handle.net/20.500.13091/2

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Citation - WoS: 3
Citation - Scopus: 6
3t2fts: a Novel Feature Transform Strategy To Classify 3d Mri Voxels and Its Application on Hgg/Lgg Classification
(MDPI, 2023) Hajmohamad, Abdulsalam; Koyuncu, Hasan
The distinction between high-grade glioma (HGG) and low-grade glioma (LGG) is generally performed with two-dimensional (2D) image analyses that constitute semi-automated tumor classification. However, a fully automated computer-aided diagnosis (CAD) can only be realized using an adaptive classification framework based on three-dimensional (3D) segmented tumors. In this paper, we handle the classification section of a fully automated CAD related to the aforementioned requirement. For this purpose, a 3D to 2D feature transform strategy (3t2FTS) is presented operating first-order statistics (FOS) in order to form the input data by considering every phase (T1, T2, T1c, and FLAIR) of information on 3D magnetic resonance imaging (3D MRI). Herein, the main aim is the transformation of 3D data analyses into 2D data analyses so as to applicate the information to be fed to the efficient deep learning methods. In other words, 2D identification (2D-ID) of 3D voxels is produced. In our experiments, eight transfer learning models (DenseNet201, InceptionResNetV2, InceptionV3, ResNet50, ResNet101, SqueezeNet, VGG19, and Xception) were evaluated to reveal the appropriate one for the output of 3t2FTS and to design the proposed framework categorizing the 210 HGG-75 LGG instances in the BraTS 2017/2018 challenge dataset. The hyperparameters of the models were examined in a comprehensive manner to reveal the highest performance of the models to be reached. In our trails, two-fold cross-validation was considered as the test method to assess system performance. Consequently, the highest performance was observed with the framework including the 3t2FTS and ResNet50 models by achieving 80% classification accuracy for the 3D-based classification of brain tumors.
Citation - Scopus: 1
Aber Performance of Ofdm-Im Systems by Ris Design in the Presence of Iqi and Α-Μ Fading
(Elsevier - Division Reed Elsevier India Pvt Ltd, 2024) Karahan, Busra; Develi, Ibrahim; Canbilen, Ayse Elif; Alsalameh, Hussam
Index modulation (IM) techniques are among the competitive candidates for fifth-generation and beyond (5GB) systems, offering new ways of conveying information thanks to their advantages such as structure flexibility and hardware convenience. Meanwhile, research on orthogonal frequency division multiplexing (OFDM) performance improvements for next-generation wireless communication systems is still intensively ongoing. Accordingly, the IM system has been adapted to OFDM, which allows additional bits of information to be transmitted through the subcarrier indices of the OFDM. Nevertheless, hardware impairments (HWIs) limit the performance of the transceiver. In the literature, reconfigurable intelligent surface (RIS) technology controls the propagation environment and enhances the quality of the received signal by modifying the phase of the incoming signal. In this paper, we investigate the effects of in-phase (I) and quadrature-phase (Q) imbalance (IQI) on RIS-based OFDM-IM transceivers motivated by the benefits of the RISs. Firstly, we present an RIS-assisted OFDM-IM model subject to transmitter and receiver IQI effects. Next, the average bit error rate (ABER) performance of the RIS-assisted OFDM-IM is calculated by the provided mathematical expressions taking the effect of IQI into account. The simulation outputs show that the designed RIS-supported scheme achieves a performance improvement compared to the traditional OFDM-IM under the effect of IQI.
Citation - WoS: 11
Citation - Scopus: 15
Accuracy Assessment of Dems Derived From Multiple Sar Data Using the Insar Technique
(SPRINGER HEIDELBERG, 2021) Karabörk, Hakan; Makineci, Hasan Bilgehan; Orhan, Osman; Karakuş, Pınar
In this study, digital elevation models (DEMs) derived from AlosPalsar data (Japanese Space Agency-JAXA), Sentinel-1A data, and Envisat ASAR data (European Space Agency-ESA) were compared by using a global navigation satellite system (GNSS). In addition, AW3D30, SRTM, and ASTER GDEM (open-access DEMs) data were also included in the accuracy evaluation. The DEM accuracies were investigated in three different terrain types, namely a plain area, mountainous area and agricultural area, and compared at elevation values on a pixel-based. The accuracy obtained from the ALOS PALSAR satellite data was found to be more reliable for all three terrain types. The standard deviation and root mean square values were calculated and compared to each other. The results of the accuracy assessments showed that the best result for the plain area was obtained with the Sentinel-1A and SRTM data, for the mountainous area was obtained with the SRTM data and for agricultural area was obtained with the ALOS PALSAR and SRTM data.
Citation - WoS: 24
Citation - Scopus: 40
An Adaptive Method for Traffic Signal Control Based on Fuzzy Logic With Webster and Modified Webster Formula Using Sumo Traffic Simulator
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2021) Ali, Muzamil Eltejani Mohammed; Durdu, Akif; Çeltek, Seyit Alperen; Yılmaz, Alper
In the past, the Webster optimal cycle time formula was limited to calculate the optimal cycle from historical data for fixed-time traffic signal control. This paper focuses on the design of an adaptive traffic signal control based on fuzzy logic with Webster and modified Webster's formula. These formulas are used to calculate the optimal cycle time depending on the current traffic situation which applying in the next cycle. The alternation of the traffic condition between two successive cycles is monitored and handled through the fuzzy logic system to compensate the fluctuation. The obtained optimal cycle time is used to determine adaptively the effective phase green times i.e. is used to determine adaptively the maximum allowable extension limit of the green phase in the next cycle. The SUMO traffic simulator is used to compare the results of the proposed adaptive control methods with fuzzy logic-based traffic control, and fixed-time Webster and modified Webster-based traffic control methods. The proposed methods are tested on an isolated intersection. In this study, real field-collected data obtained from three, four, and five approaches intersections in Kilis/Turkey are used to test the performance of the proposed methods. In addition, to examine the efficiency of the proposed techniques at heavy demands, the arbitrary demands are generated by SUMO for a four approaches intersection. The obtained simulation results indicate that the proposed methods overperform the fixed time and fuzzy logic-based traffic control methods in terms of average vehicular delay, speed, and travel time.
Citation - WoS: 5
Addendum: Measurement and Qcd Analysis of Double-Differential Inclusive Jet Cross Sections in Proton-Proton Collisions at Root S=13 Tev
(Springer, 2022) Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Dragicevic, M.; Del Valle, A. Escalante; Gürpınar Güler, Emine; Güler, Yalçın
The QCD analysis at NNLO is repeated by using the NNLO interpolation grids for the double-differential inclusive jet cross section [1], which were released after the journal publication of the original analysis. The NNLOJET calculation used to derive these grids is based on the leading-colour and leading-flavour-number approximation and does not include the most recent subleading colour contributions. However, these contributions were reported in ref. [2] to be very small in inclusive jet production, in particular for a jet size of R = 0.7. The grids also contain an estimate of the numerical integration uncertainty of around 1% or less. To account for point-to-point fluctuations, this uncertainty, after consultation with the authors of NNLOJET, has been increased by a factor of two; however, its impact in the fit is negligible. A comparison of the measurement with predictions using various PDFs is shown in figure 1. Although the PDF parametrisation remains identical, higher precision in PDF and QCD parameters is expected by using NNLO grids consistently in the QCD analysis. These new results supersede those obtained by using the k-factor technique.
Citation - WoS: 3
Citation - Scopus: 3
Adjacent-Net: Deep Learning Classification of Adjacent Buildings for Assessing Pounding Effects Using Building Facade Images in Earthquake-Prone Regions
(Elsevier Science inc, 2025) Ekici, M. Yusa; Yavariabdi, Amir; Dogan, Gamze; Arslan, M. Hakan
In earthquake-prone areas, it is extremely important to carry out risk analyses of existing buildings and to take proactive measures in advance of potential earthquakes. Despite the availability of Rapid Seismic Assessment Methods (RSAMs), prioritising the seismic risk of buildings is a significant challenge due to the large number of residential buildings in the building stock. In RSAMs, many factors are taken into consideration to determine the earthquake risk priority. While specific construction conditions determine the risk parameters for the considered structures, one of them is the possible pounding effects (collision) of adjacent buildings. The fact that RSAMs have many evaluation parameters makes it difficult in site survey for technical experts to make decisions in some cases. Therefore, it is very important to perform these operations with software support. Based on this motivation, this study aims to perform pre-earthquake risk analysis of residential reinforced concrete buildings by assisting expert engineers (or facilitating the decision-making process in the absence of technical expertise) and to estimate the adjacent building parameter using building facade images for risk prioritisation. To achieve these objectives, a novel deep learning Convolutional Neural Network (CNN) model, named Adjacent-Net, is designed and developed to classify building facade images into adjacent or non-adjacent categories. The performance of Adjacent-Net is compared with various state-of-the-art CNN models such as DarkNet-53, EfficientNet, Inception ResNetV2, NasNet Large, ResNet-101, ShuffleNet, SqueezeNet, VGG-19, and Xception. For evaluation purposes, a dataset comprising 6170 building facade images is collected, and the results indicate that Adjacent-Net can accurately extract building adjacency parameters from images with an accuracy rate of approximately 98 %. This underscores the potential of intelligent systems in detecting collision scenarios, assessing the seismic risk of structures, and determining critical geometric parameters of buildings.
Citation - WoS: 9
Citation - Scopus: 11
Adrenal Tumor Segmentation Method for Mr Images
(ELSEVIER IRELAND LTD, 2018) Barstuğan, Mücahid; Ceylan, Rahime; Asoğlu, Semih; Cebeci, Hakan; Koplay, Mustafa
Background and objective: Adrenal tumors, which occur on adrenal glands, are incidentally determined. The liver, spleen, spinal cord, and kidney surround the adrenal glands. Therefore, tumors on the adrenal glands can be adherent to other organs. This is a problem in adrenal tumor segmentation. In addition, low contrast, non-standardized shape and size, homogeneity, and heterogeneity of the tumors are considered as problems in segmentation. Methods: This study proposes a computer-aided diagnosis (CAD) system to segment adrenal tumors by eliminating the above problems. The proposed hybrid method incorporates many image processing methods, which include active contour, adaptive thresholding, contrast limited adaptive histogram equalization (CLAHE), image erosion, and region growing. Results: The performance of the proposed method was assessed on 113 Magnetic Resonance (MR) images using seven metrics: sensitivity, specificity, accuracy, precision, Dice Coefficient, Jaccard Rate, and structural similarity index (SSIM). The proposed method eliminates some of the discussed problems with success rates of 74.84%, 99.99%, 99.84%, 93.49%, 82.09%, 71.24%, 99.48% for the metrics, respectively. Conclusions: This study presents a new method for adrenal tumor segmentation, and avoids some of the problems preventing accurate segmentation, especially for cyst-based tumors. (C) 2018 Elsevier B.V. All rights reserved.
Citation - WoS: 42
Citation - Scopus: 49
Adsorption of Malachite Green and Methyl Violet 2b by Halloysite Nanotube: Batch Adsorption Experiments and Box-Behnken Experimental Design
(Elsevier Ltd, 2022) Altun, Türkan; Ecevit, Hüseyin
Dyes constitute a significant part of the pollutants in industrial wastewater. In this study, halloysite nanotube (HNT) was used for adsorption of malachite green and methyl violet 2B dyes from the solution. Using batch adsorption experiments and response surface method, parameters affecting adsorption have been optimized. As a consequence of the batch experiments, after 60 min, the adsorption equilibrium state was achieved at 3 g L?1 HNT dosage, 125 mg L?1 dye concentration and natural solution pH. Temperature did not significantly affect the adsorption. The adsorption equilibrium data can be said to have fitted the Langmuir, Freundlich, Dubinin-Radushkevich and Temkin isotherms well for the both dyes. The Langmuir maximum monolayer malachite green and methyl violet 2B adsorption capacities (As) of HNT are 74.95 mg g?1 and 67.87 mg g?1, respectively. Adsorption processes are more consistent with the pseudo-second-order kinetic model. In addition, both intra-particle diffusion and film diffusion are effective as rate-determining steps in adsorption. Thermodynamic calculations showed that the adsorption is exothermic and spontaneous. The regeneration of HNT after adsorption was confirmed in five cycles. By using the Box-Behnken response surface method, the parameters affecting the adsorption process were modeled, the effects of these parameters on the adsorption efficiency were expressed mathematically and the optimum operating parameters were determined. © 2022
Citation - WoS: 3
Citation - Scopus: 3
Adsorption-Assisted Photocatalytic Degradation of Anionic Direct Yellow-50 and Cationic Methylene Blue Dyes by Chemically Synthesized Poly(1,5-Diaminoanthraquinone
(Springer, 2025) Akıllı, A.; Özler, A.; Taymaz, B.H.; Hancı, A.; Eskizeybek, V.; Kamış, H.
Conducting polymers renowned for their exceptional photocatalytic activity, conductivity, and visible-light absorption capabilities present a compelling alternative for advanced photocatalytic applications. In this regard, the creation of conductive polymers of the next generation has enormous promise for improving energy efficiency as well as solving environmental issues. In this study, the conductive polymer poly(1,5-diaminoanthraquinone) (PDAAQ) with a band gap of 1.28 eV and an electrical conductivity of 1.23 S/cm was successfully synthesized via chemical oxidative polymerization using ammonium peroxydisulfate as an oxidant and perchloric acid as an initiator in an acetonitrile polymerization medium. The adsorption-assisted photocatalytic performance of PDAAQ has been investigated in cationic methylene blue (MB) and an anionic direct yellow (DY) dye under visible irradiation. The effect of polymerization medium, oxidant type, polymerization time, and monomer oxidant ratio on adsorption-assisted photocatalytic degradation of MB was investigated. The synthesized PDAAQ polymer demonstrates exceptional photocatalytic performance, completely degrading MB and DYE dyes under visible light illumination in 6 and 8 min through an adsorption-assisted photocatalysis mechanism. Besides, the photocatalytic dye degradation performance of PDAAQ was investigated for the degradation of synthetic wastewater (SWW) under visible light. The PDAAQ polymer proves to be an effective photocatalyst for photocatalytic applications, showcasing exceptional potential in degrading model dyes and treating synthetic wastewater. © The Author(s) 2025.
Citation - WoS: 50
Citation - Scopus: 55
Advanced Oxidation of Landfill Leachate: Removal of Micropollutants and Identification of By-Products
(ELSEVIER, 2021) Ateş, Havva; Argun, Mehmet Emin
Landfill leachate contains several macropollutants and micropollutants that cannot be removed efficiently by conventional treatment processes. Therefore, an advanced oxidation process is a promising step in post or pre-treatment of leachate. In this study, the effects of Fenton and ozone oxidation on the removal of 16 emerging micropollutants including polycyclic aromatic hydrocarbons (PAHs), phthalates, alkylphenols and pesticides were investigated. The Fenton and ozone oxidation of the leachate were performed with four (reaction time: 20-90 min, Fe(II) dose: 0.51-2.55 g/L, H2O2 dose: 5.1-25.5 g/L and pH: 3-5) and two (ozonation time: 10-130 min and pH: 4-10) independent variables, respectively. Among these operating conditions, reaction time played more significant role (p-value < 0.05) in eliminating di-(2-Ethylhexyl) phthalate, 4-nonylphenol and 4-tert-octylphenol for both processes. The results showed that Fenton and ozone oxidation processes had a high degradation potential for micropollutants except for the PAHs including four and more rings. Removal efficiencies of micropollutants by ozone and Fenton oxidation were determined in the range of 5-100%. Although the removal efficiencies of chemical oxygen demand (COD) and some micropollutants such as phthalates were found much higher in the Fenton process than ozonation, the degradation products occurred during the Fenton oxidation were a higher molecular weight. Moreover, the oxidation intermediates for the both processes were found as mainly benzaldehyde, pentanoic acid and hydro cinnamic acid as well as derivatives of naphthalenone and naphthalenediol. Also, acid ester with higher molecular weight, naphthalene-based and phenolic compounds were detected in the Fenton oxidation.
Advancing Remote Sensing with Few-Shot Learning: A Comprehensive Review of Methods, Challenges, and Future Directions
(Wiley, 2025) Aslan, Muhammet Fatih; Sabanci, Kadir; Durdu, Akif; Kaousar, Rehana
In this review, the details and developments of few-shot learning (FSL) techniques in different remote sensing (RS) studies including change monitoring, disaster management, urban monitoring, and agriculture are discussed in detail. Furthermore, a categorization is made by dividing FSL methods into three categories (metric-based, optimization-based, and transfer learning approaches) and considering hybrid approaches. Special attention is given to episodic training and meta-learning approaches that provide rapid adaptation to new classes with minimal examples. Furthermore, the integration of explainable artificial intelligence (XAI) and its real-time application capabilities are discussed. Important issues such as domain shift, class imbalance, and high dimensionality are discussed. Recent refinements such as task-level learning, data augmentation, and multimodal integration are examined. Finally, a coherent framework is suggested for further studies and practical FSL applications in the context of RS. As a result, it provides a more comprehensive perspective than previous reviews. This review aimed to guide future research in the integration of FSL with RS applications by analyzing the existing literature and pointing out important research gaps.
Citation - WoS: 8
Citation - Scopus: 12
The Aerodynamic Effects of Blade Pitch Angle on Small Horizontal Axis Wind Turbines
(Emerald Group Publishing Ltd, 2022) Kaya, Mehmet Numan; Uzol, Oguz; Ingham, Derek; Köse, Faruk; Büyükzeren, Rıza
Purpose The purpose of this paper is to thoroughly investigate the aerodynamic effects of blade pitch angle on small scaled horizontal axis wind turbines (HAWTs) using computational fluid dynamics (CFD) method to find out the sophisticated effects on the flow phenomena and power performance. Design/methodology/approach A small HAWT is used as a reference to validate the model and examine the aerodynamic effects. The blade pitch angle was varied between +2 and -6 degrees, angles which are critical for the reference wind turbine in terms of performance, and the CFD simulations were performed at different tip speed ratio values, lambda = 2, 3, 4, 5, 6, 7, 9 and 10.5 to cover the effects in various conditions. Results are examined in two different aspects, namely, general performance and the flow physics. Findings The power performance varies significantly according to the tip speed ratio; the power coefficient increases up to a certain pitch angle at the design tip speed ratio (lambda = 6); however, between lambda = 2 and 4, the more the blade is pitched downwards, the larger is the power coefficient, the smaller is the thrust coefficient. Similarly, for tip speed ratios higher than lambda = 8, the positive effect of the low pitch angles on the power coefficient at lambda = 6 reverses. The flow separation location moves close to the leading edge at low tip speed ratios when the blade is pitched upwards and the also tip vortices become more intense. In conclusion, the pitch control can significantly contribute to the performance of small HAWTs depending on different conditions. Originality/value In the literature, only very little attention has been paid to the aerodynamic effects of pitch angle on HAWTs, and no such study is available about the effects on small HAWTs. The change of blade pitch angle was maintained at only one degree each time to capture even the smallest aerodynamic effects, and the results are presented in terms of the power performance and flow physics.
Citation - WoS: 25
Citation - Scopus: 29
Aerogels as Promising Materials for Antibacterial Applications: a Mini-Review
(ROYAL SOC CHEMISTRY, 2021) Kaya Güzel, Gülcihan; Aznar, Elena; Deveci, Hüseyin; Martinez-Manez, Ramon
The increasing cases of bacterial infections originating from resistant bacteria are a serious problem globally and many approaches have been developed for different purposes to treat bacterial infections. Aerogels are a novel class of smart porous materials composed of three-dimensional networks. Recently, aerogels with the advantages of ultra-low density, high porosity, tunable particle and pore sizes, and biocompatibility have been regarded as promising carriers for the design of delivery systems. Recently, aerogels have also been provided with antibacterial activity through loading of antibacterial agents, incorporation of metal/metal oxides and via surface functionalization and coating with various functional groups. In this mini-review, the synthesis of aerogels from both conventional and low-cost precursors is reported and examples of aerogels displaying antibacterial properties are summarized. As a result, it is clear that the encouraging antibacterial performance of aerogels promotes their use in many antibacterial applications, especially in the food industry, pharmaceutics and medicine.
Citation - WoS: 29
Citation - Scopus: 54
Alexnet Architecture Variations With Transfer Learning for Classification of Wound Images
(Elsevier B.V., 2023) Eldem, H.; Ülker, E.; Işıklı, O.Y.
In medical world, wound care and follow-up is one of the issues that are gaining importance to work on day by day. Accurate and early recognition of wounds can reduce treatment costs. In the field of computer vision, deep learning architectures have received great attention recently. The achievements of existing pre-trained architectures for describing (classifying) data belonging to many image sets in the real world are primarily addressed. However, to increase the success of these architectures in a certain area, some improvements and enhancements can be made on the architecture. In this paper, the classification of pressure and diabetic wound images was performed with high accuracy. The six different new AlexNet architecture variations (3Conv_Softmax, 3Conv_SVM, 4Conv_Softmax, 4Conv_SVM, 6Conv_Softmax, 6Conv_SVM) were created with a different number of implementations of Convolution, Pooling, and Rectified Linear Activation (ReLU) layers. Classification performances of the proposed models are investigated by using Softmax classifier and SVM classifier separately. A new original Wound Image Database are created for performance measures. According to the experimental results obtained for the Database, the model with 6 Convolution layers (6Conv_SVM) was the most successful method among the proposed methods with 98.85% accuracy, 98.86% sensitivity, and 99.42% specificity. The 6Conv_SVM model was also tested on diabetic and pressure wound images in the public medetec dataset, and 95.33% accuracy, 95.33% sensitivity, and 97.66% specificity values were obtained. The proposed method provides high performance compared to the pre-trained AlexNet architecture and other state-of-the-art models in the literature. The results showed that the proposed 6Conv_SVM architecture can be used by the relevant departments in the medical world with good performance in medical tasks such as examining and classifying wound images and following up the wound process. © 2023 Karabuk University
Citation - WoS: 14
Citation - Scopus: 14
All-Dry Synthesis of Poly(2-Ethylhexyl Acrylate) Nanocoatings Using Initiated Chemical Vapor Deposition Method
(ELSEVIER SCIENCE SA, 2019) Şakalak, Hüseyin; Karaman, Mustafa
In this study, Poly(2-ethylhexyl acrylate) (PEHA) thin films were deposited on different substrates by initiated chemical vapor deposition (iCVD) technique. Being a long alkyl chain acrylate with a suitably low glass transition temperature, PEHA is an important member of acrylates family, which is used extensively in adhesives, paints, and coating applications. In iCVD, use of the tert-butyl peroxide as an initiator allowed a deposition rate of 155 nm/min at a filament temperature of 280 degrees C. Precursor flow ratios, filament and substrate temperatures were found to be important parameters that effect the deposition rates. The negative relation between substrate temperature and deposition rates implied an adsorption limited kinetics. FTIR and XPS analyses of the deposited films confirmed that the chemical functionality of the EHA monomer preserved well after iCVD. It was also revealed that the as-deposited films are smooth, uniform and optically transparent. PEHA film deposited by iCVD on glass improved the optical transmittance of glass, by acting as an anti-reflection coating due to its suitable refractive index of 1.45.
Analysing the Relationship Between Space Quality and Place Attachment in Urban Coasts Using Structural Equation Modelling: The Antalya Konyaaltı Case
(Routledge Journals, Taylor & Francis Ltd, 2025) Cevrimli, Begum Akoz; Ulusoy, Mine
The physical and social characteristics of urban design can influence the degree to which users develop attachment to a place. This study aims to identify spatial quality factors in urban coastal areas, analyse their effects on place attachment and provide a theoretical framework for the design of urban coastal spaces. Conducted in the Antalya-Konyaalt & imath; urban coastal area, the study identified quality factors through Exploratory and Confirmatory Factor Analyses, thereby developing a valid and reliable measurement tool. Place attachment levels were assessed based on the scale developed by Williams and Vaske (Williams, D. R., & Vaske, J. J. (2003). The measurement of place attachment: validity and generalizability of a psychometric approach. Forest Science, 49(6), 830-840. https://doi.org/10.1093/forestscience/49.6.830). Survey data were collected from coastal subareas that differ in design characteristics and analysed using ANOVA, regression analysis and structural equation modelling (SEM). The findings indicate that the factors alone are insufficient to explain place attachment; however, the structural model established through SEM reveals these relationships with strong model fit values. While all factors were found to have a positive effect in the regression analysis, SEM results showed that particularly green space quality, vibrancy, safety and ease of movement significantly influence place attachment. The observed negative relationship between green space quality and place attachment suggests that the physical qualities of these spaces alone are not sufficient to foster attachment, especially in the presence of deficiencies in accessibility, continuity and other spatial attributes. As a result, the combined use of different analytical techniques has provided an opportunity to evaluate the phenomenon of place attachment in coastal spaces in a more comprehensive and in-depth manner. This study provides a theoretical foundation for the relationship between coastal spatial quality factors and place attachment, offering a substantial basis for developing design strategies specific to urban coastal contexts.
Citation - WoS: 27
Citation - Scopus: 34
Analysis of Effect Factors on Thermoelectric Generator Using Taguchi Method
(ELSEVIER SCI LTD, 2020) Terzioğlu, Hakan
Due to technological developments in recent years, the need for domestic and industrial electric power is increasing day by day. Alternative energy resources have become more important to reduce production costs by converting waste energy into electricity. In this study, a research was carried out to increase the efficiency and on the factors which were effective in Thermoelectric Generators (TEG) used in the production of electrical energy by using thermal sources from alternative energy sources. In this study, the effects of heat transfer performance of the materials (copper, aluminum and brass) on which thermal water is carried, and the effects of water pressure and velocity on the performance of TEGs were investigated. Taguchi method was used to determine the performance effects in the most accurate way. Taguchi method used three levels with three factors: material (copper, aluminum and brass), engine speed (I, II and III) and water pressure (1-2.5-3.5 bar). In addition, in the Taguchi method, the orthogonal array was used and the optimum operation time was significantly reduced. In this study, TEG1-12706 and TEG1-12710 were performed in 2 different TEGs. 27 experiments were carried out for each TEG under different materials, speed and pressure of water with the experiment set up in this study. When the test results were analyzed by Taguchi method, it was determined that the material was the most important factor in determining the output power and efficiency in the production of electrical energy by using TEG (approx. 89%) and it was seen that the pressure and engine speed had almost no role. (C) 2019 Published by Elsevier Ltd.
Citation - WoS: 17
Citation - Scopus: 19
Analysis of Electrospinning and Additive Effect on ? Phase Content of Electrospun Pvdf Nanofiber Mats for Piezoelectric Energy Harvester Nanogenerators
(Institute of Physics, 2022) Oflaz, Kamil; Özaytekin, İlkay
Harvesting energy with piezoelectric nanoparticles enables the development of self-powered devices. Poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF) has been widely used in a variety of fields due to its superior piezoelectric properties. PVDF’s piezoelectric performance is affected by the presence of polar phase in the crystalline structure. The electrospinning process was used in this study to achieve high ? phase ratios in the PVDF crystalline structure using various additives (graphene, boron nitride, and quartz (SiO2)). The Taguchi experimental design method was used to determine the most significant parameters affecting ? phase content from seven factors, as well as the optimal levels of the significant factors. The Fourier transform infrared, x-ray diffraction, scanning electron microscopy, energy-dispersive x-ray and differential scanning calorimetry analyses were used to characterize the composite PVDF nanofiber mats produced under optimal conditions, and the output voltage was measured using an oscilloscope. The composite PVDF nanofiber mat with the highest ? phase concentration demonstrated a maximum output voltage of 8.68 V under optimal conditions, indicating that it outperformed than pure PVDF under equal electrospinning conditions. © 2022 IOP Publishing Ltd.
Citation - WoS: 3
Citation - Scopus: 6
Analysis of Seasonal Rainfall Variability With Innovative Graphical Methods of Konya Closed Basin, Türkiye
(Elsevier Ltd, 2024) Koycegiz, C.; Buyukyildiz, M.
This study looked into the variability of seasonal rainfall in the semi-arid Konya Closed Basin (KCB), a water-limited region with high exploitation demand for water resources due to agricultural activities. In the study, seasonal precipitation data of eleven stations in the basin for the period 1971–2020 were used and analyzed with four trend methods (Şen-ITA, CWTSD, IPTA, and TPSC). Visual and statistical findings from the analyses showed generally increasing trends in winter and summer precipitation and decreasing trends in spring precipitation in the basin. In autumn precipitation, according to Şen-ITA, there is an increasing trend in seven stations and a decreasing trend in four stations, while according to CWTSD, there is an increasing trend in six stations and a decreasing trend in five stations. Based on the arithmetic mean IPTA graphs, Winter-Spring transitions in all stations occur from a rising trend region to a falling trend region, but Spring-Summer transitions take the reverse direction. In the standard deviation IPTA graphs, similar transitions in the trend regions are predominant. To the mean and standard deviation TPSC graphs, most of the stations generally have similar behavior. Spring-Summer transition arrows are dominant in Zone III, while Summer-Autumn and Autumn-Winter transitions are dominant in Zone I. Although Winter-Spring transitions are variable, they are more intense in Zone I and III. CWTSD and Şen-ITA methods are also consistent with the results obtained from IPTA graphs, both visually and numerically. © 2024 Elsevier Ltd
Citation - WoS: 9
Citation - Scopus: 10
An Analysis of Terrestrial Water Storage Changes of a Karstic, Endorheic Basin in Central Anatolia, Turkey
(Elsevier B.V., 2023) Köycegiz, C.; Sen, O.L.; Buyukyildiz, M.
Water budget components of endorheic basins of semi-arid and karstic characters are difficult to assess. In this study, we attempt to estimate the water budget components of the Konya Endorheic Basin (KEB), which is a semi-arid, karstic basin in central Anatolia, using The Gravity Recovery and Climate Experiment mission (GRACE) observations and Global Land Data Assimilation System (GLDAS) data over the period 2002-2019. We also investigate the trends and sub-trends in the time series of the hydrometeorological parameters. The results indicate that the available water potential in the basin has a decreasing trend over the study period. Precipitation and evapotranspiration show increasing trends in the basin, however, the other hydrometeorological parameters demonstrate decreasing trends. Both Terrestrial Water Storage Anomaly (TWSA) and groundwater level decrease significantly (20.21 mm/yr and 122.34 mm/yr, respectively). The dry 2008 and subsequent wet year created a hydrological breaking point in the time series. The weights of soil moisture and groundwater storages are relatively large amongst the TWSA components (49.61% and 33.12%, respectively). The surface water storage anomaly comes at the third place with a 14% weight. It is assessed that the groundwater storage system responds to precipitation with a delay of 6 months. Limestone zones respond more sharply to groundwater depletion than alluvial zones. It should be noted that the GRACE and GLDAS data could be used together to successfully estimate the water budget components for sustainable management of the limited water resources of the basin. © 2023

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